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/*
* Copyright (c) 2023, Peter Abeles. All Rights Reserved.
*
* This file is part of Efficient Java Matrix Library (EJML).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.ejml.simple.ops;
import javax.annotation.Generated;
import org.ejml.concurrency.EjmlConcurrency;
import org.ejml.data.*;
import org.ejml.ops.MatrixIO;
import org.ejml.simple.ConvertToDenseException;
import org.ejml.simple.ConvertToImaginaryException;
import org.ejml.simple.SimpleSparseOperations;
import org.ejml.sparse.csc.CommonOps_FSCC;
import org.ejml.sparse.csc.CommonOps_MT_FSCC;
import org.ejml.sparse.csc.MatrixFeatures_FSCC;
import org.ejml.sparse.csc.NormOps_FSCC;
import org.ejml.sparse.csc.mult.Workspace_MT_FSCC;
import pabeles.concurrency.GrowArray;
import java.io.PrintStream;
import static org.ejml.concurrency.EjmlConcurrency.useConcurrent;
/**
* Implementation of {@link org.ejml.simple.SimpleOperations} for {@link FMatrixSparseCSC}.
*
* @author Peter Abeles
*/
@Generated("org.ejml.simple.ops.SimpleOperations_DSCC")
public class SimpleOperations_FSCC implements SimpleSparseOperations {
// Workspace variables
public transient IGrowArray gw = new IGrowArray();
public transient FGrowArray gx = new FGrowArray();
// Workspace for concurrent algorithms
public transient GrowArray workspaceMT = new GrowArray<>(Workspace_MT_FSCC::new);
public transient GrowArray workspaceA = new GrowArray<>(FGrowArray::new);
@Override public void set( FMatrixSparseCSC A, int row, int column, /**/double value ) {
A.set(row, column, (float)value);
}
@Override public void set( FMatrixSparseCSC A, int row, int column, /**/double real, /**/double imaginary ) {
throw new ConvertToImaginaryException();
}
@Override public /**/double get( FMatrixSparseCSC A, int row, int column ) {
return A.get(row, column);
}
@Override public void get( FMatrixSparseCSC A, int row, int column, /**/Complex_F64 value ) {
value.real = A.get(row, column);
value.imaginary = 0;
}
@Override public /**/double getReal( FMatrixSparseCSC A, int row, int column ) {
return A.get(row, column);
}
@Override public /**/double getImaginary( FMatrixSparseCSC A, int row, int column ) {
return 0;
}
@Override public void fill( FMatrixSparseCSC A, /**/double value ) {
if (value == 0) {
A.zero();
} else {
throw new ConvertToDenseException();
}
}
@Override public void transpose( FMatrixSparseCSC input, FMatrixSparseCSC output ) {
CommonOps_FSCC.transpose(input, output, gw);
}
@Override public void mult( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
if (useConcurrent(A) || useConcurrent(B)) {
CommonOps_MT_FSCC.mult(A, B, output, workspaceMT);
} else {
CommonOps_FSCC.mult(A, B, output);
}
}
@Override public void multTransA( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
var At = new FMatrixSparseCSC(1, 1);
CommonOps_FSCC.transpose(A, At, gw);
if (useConcurrent(A) || useConcurrent(B)) {
CommonOps_MT_FSCC.mult(A, B, output, workspaceMT);
} else {
CommonOps_FSCC.mult(At, B, output, gw, gx);
}
}
@Override public void extractDiag( FMatrixSparseCSC input, FMatrixRMaj output ) {
CommonOps_FSCC.extractDiag(input, output);
}
@Override public void multTransA( FMatrixSparseCSC A, FMatrixRMaj B, FMatrixRMaj output ) {
if (useConcurrent(A) || useConcurrent(B)) {
CommonOps_MT_FSCC.multTransA(A, B, output, workspaceA);
} else {
CommonOps_FSCC.multTransA(A, B, output, null);
}
}
@Override public void mult( FMatrixSparseCSC A, FMatrixRMaj B, FMatrixRMaj output ) {
if (useConcurrent(A)) {
CommonOps_MT_FSCC.mult(A, B, output, workspaceA);
} else {
CommonOps_FSCC.mult(A, B, output);
}
}
@Override public void kron( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
// CommonOps_FSCC.kron(A,B,output);
throw new RuntimeException("Unsupported for DSCC. Make a feature request if you need this!");
}
@Override public void plus( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
if (EjmlConcurrency.useConcurrent(A)) {
CommonOps_MT_FSCC.add(1, A, 1, B, output, workspaceMT);
} else {
CommonOps_FSCC.add(1, A, 1, B, output, null, null);
}
}
@Override public void minus( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
if (EjmlConcurrency.useConcurrent(A)) {
CommonOps_MT_FSCC.add(1, A, -1, B, output, workspaceMT);
} else {
CommonOps_FSCC.add(1, A, -1, B, output, null, null);
}
}
@Override public void minus( FMatrixSparseCSC A, /**/double b, FMatrixSparseCSC output ) {
throw new ConvertToDenseException();
}
@Override public void plus( FMatrixSparseCSC A, /**/double b, FMatrixSparseCSC output ) {
throw new ConvertToDenseException();
}
@Override public void plus( FMatrixSparseCSC A, /**/double beta, FMatrixSparseCSC b, FMatrixSparseCSC output ) {
if (useConcurrent(A) || useConcurrent(b)) {
CommonOps_MT_FSCC.add(1, A, (float)beta, b, output, workspaceMT);
} else {
CommonOps_FSCC.add(1, A, (float)beta, b, output, gw, gx);
}
}
@Override
public void plus( /**/double alpha, FMatrixSparseCSC A, /**/double beta, FMatrixSparseCSC b, FMatrixSparseCSC output ) {
if (useConcurrent(A) || useConcurrent(b)) {
CommonOps_MT_FSCC.add((float)alpha, A, (float)beta, b, output, workspaceMT);
} else {
CommonOps_FSCC.add((float)alpha, A, (float)beta, b, output, gw, gx);
}
}
@Override public /**/double dot( FMatrixSparseCSC A, FMatrixSparseCSC v ) {
return CommonOps_FSCC.dotInnerColumns(A, 0, v, 0, gw, gx);
}
@Override public void scale( FMatrixSparseCSC A, /**/double val, FMatrixSparseCSC output ) {
CommonOps_FSCC.scale((float)val, A, output);
}
@Override public void divide( FMatrixSparseCSC A, /**/double val, FMatrixSparseCSC output ) {
CommonOps_FSCC.divide(A, (float)val, output);
}
@Override public boolean invert( FMatrixSparseCSC A, FMatrixSparseCSC output ) {
return solve(A, output, CommonOps_FSCC.identity(A.numRows, A.numCols));
}
@Override public void setIdentity( FMatrixSparseCSC A ) {
CommonOps_FSCC.setIdentity(A);
}
@Override public void pseudoInverse( FMatrixSparseCSC A, FMatrixSparseCSC output ) {
throw new RuntimeException("Unsupported");
}
@Override public boolean solve( FMatrixSparseCSC A, FMatrixSparseCSC X, FMatrixSparseCSC B ) {
return CommonOps_FSCC.solve(A, X, B);
}
public boolean solve( FMatrixSparseCSC A, FMatrixRMaj X, FMatrixRMaj B ) {
return CommonOps_FSCC.solve(A, X, B);
}
@Override public void zero( FMatrixSparseCSC A ) {
A.zero();
}
@Override public /**/double normF( FMatrixSparseCSC A ) {
return NormOps_FSCC.normF(A);
}
@Override public /**/double conditionP2( FMatrixSparseCSC A ) {
throw new RuntimeException("Unsupported");
}
@Override public /**/double determinant( FMatrixSparseCSC A ) {
return CommonOps_FSCC.det(A);
}
@Override public /**/double trace( FMatrixSparseCSC A ) {
return CommonOps_FSCC.trace(A);
}
@Override public void setRow( FMatrixSparseCSC A, int row, int startColumn, /**/double... values ) {
// TODO Update with a more efficient algorithm
for (int i = 0; i < values.length; i++) {
A.set(row, startColumn + i, (float)values[i]);
}
// check to see if value are zero, if so ignore them
// Do a pass through the matrix and see how many elements need to be added
// see if the existing storage is enough
// If it is enough ...
// starting from the tail, move a chunk, insert, move the next chunk, ...etc
// If not enough, create new arrays and construct it
}
@Override public void setColumn( FMatrixSparseCSC A, int column, int startRow, /**/double... values ) {
// TODO Update with a more efficient algorithm
for (int i = 0; i < values.length; i++) {
A.set(startRow + i, column, (float)values[i]);
}
}
@Override public /**/double[] getRow( FMatrixSparseCSC A, int row, int col0, int col1 ) {
var v = new /**/double[col1 - col0];
// Exhaustively search every column in the allowed range for rows that match the target
// If a match is found copy it's value
for (int col = col0; col < col1; col++) {
int rowIdx0 = A.col_idx[col];
int rowIdx1 = A.col_idx[col + 1];
for (int i = rowIdx0; i < rowIdx1; i++) {
if (row != A.nz_rows[i])
continue;
v[col - col0] = A.nz_values[i];
}
}
return v;
}
@Override public /**/double[] getColumn( FMatrixSparseCSC A, int col, int row0, int row1 ) {
var v = new /**/double[row1 - row0];
// Go through the target column and find all row elements within the allowed range
int rowIdx0 = A.col_idx[col];
int rowIdx1 = A.col_idx[col + 1];
for (int i = rowIdx0; i < rowIdx1; i++) {
int row = A.nz_rows[i];
if (row < row0 || row >= row1)
continue;
v[row - row0] = A.nz_values[i];
}
return v;
}
@Override
public void extract( FMatrixSparseCSC src, int srcY0, int srcY1, int srcX0, int srcX1, FMatrixSparseCSC dst, int dstY0, int dstX0 ) {
CommonOps_FSCC.extract(src, srcY0, srcY1, srcX0, srcX1, dst, dstY0, dstX0);
}
@Override public FMatrixSparseCSC diag( FMatrixSparseCSC A ) {
FMatrixSparseCSC output;
if (MatrixFeatures_FSCC.isVector(A)) {
int N = Math.max(A.numCols, A.numRows);
output = new FMatrixSparseCSC(N, N);
CommonOps_FSCC.diag(output, A.nz_values, 0, N);
} else {
int N = Math.min(A.numCols, A.numRows);
output = new FMatrixSparseCSC(N, 1);
CommonOps_FSCC.extractDiag(A, output);
}
return output;
}
@Override public boolean hasUncountable( FMatrixSparseCSC M ) {
return MatrixFeatures_FSCC.hasUncountable(M);
}
@Override public void changeSign( FMatrixSparseCSC a ) {
CommonOps_FSCC.changeSign(a, a);
}
@Override public /**/double elementMax( FMatrixSparseCSC A ) {
return CommonOps_FSCC.elementMax(A);
}
@Override public /**/double elementMin( FMatrixSparseCSC A ) {
return CommonOps_FSCC.elementMin(A);
}
@Override public /**/double elementMaxAbs( FMatrixSparseCSC A ) {
return CommonOps_FSCC.elementMaxAbs(A);
}
@Override public /**/double elementMinAbs( FMatrixSparseCSC A ) {
return CommonOps_FSCC.elementMinAbs(A);
}
@Override public /**/double elementSum( FMatrixSparseCSC A ) {
return CommonOps_FSCC.elementSum(A);
}
@Override public void elementMult( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
CommonOps_FSCC.elementMult(A, B, output, null, null);
}
@Override public void elementDiv( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
throw new ConvertToDenseException();
}
@Override public void elementPower( FMatrixSparseCSC A, FMatrixSparseCSC B, FMatrixSparseCSC output ) {
throw new ConvertToDenseException();
}
@Override public void elementPower( FMatrixSparseCSC A, /**/double b, FMatrixSparseCSC output ) {
throw new ConvertToDenseException();
}
@Override public void elementExp( FMatrixSparseCSC A, FMatrixSparseCSC output ) {
throw new ConvertToDenseException();
}
@Override public void elementLog( FMatrixSparseCSC A, FMatrixSparseCSC output ) {
throw new ConvertToDenseException();
}
@Override public boolean isIdentical( FMatrixSparseCSC A, FMatrixSparseCSC B, /**/double tol ) {
return MatrixFeatures_FSCC.isEqualsSort(A, B, (float)tol);
}
@Override public void print( PrintStream out, Matrix mat, String format ) {
MatrixIO.print(out, (FMatrixSparseCSC)mat, format);
}
@Override public void elementOp( FMatrixSparseCSC A, ElementOpReal op, FMatrixSparseCSC output ) {
// Ensure the output has the same non-zero elements as A
output.copyStructure(A);
for (int col = 0; col < A.numCols; col++) {
int idx0 = A.col_idx[col];
int idx1 = A.col_idx[col + 1];
for (int i = idx0; i < idx1; i++) {
int row = A.nz_rows[i];
float value = A.nz_values[i];
output.nz_values[i] = (float)op.op(row, col, value);
}
}
}
@Override public void elementOp( FMatrixSparseCSC A, ElementOpComplex op, FMatrixSparseCSC output ) {
throw new ConvertToImaginaryException();
}
}